Very high CPU Steal Time with "t2.micro" located on "us-east-2b"

Greeting

Hi, Flower Shop Guy!

Thanks for bringing up this issue about high CPU Steal Time on your t2.micro instance in us-east-2b. I can imagine how frustrating those lags must be, especially when turning the instance off and on only provides temporary relief. Let’s dive into the root cause and steps to resolve it! 🌸

---

Clarifying the Issue

It sounds like your t2.micro instance is experiencing significant performance degradation due to high CPU Steal Time. Steal Time often indicates that the hypervisor hosting your virtual server is under heavy load, causing your instance to compete with others for physical CPU resources. The fact that restarting temporarily helps suggests the issue is tied to the underlying host, but the problem returns when the same host becomes overloaded again.

This issue is especially common with smaller instance types like t2.micro, as their limited resources can quickly be affected by host contention. Understanding why this happens and exploring more sustainable solutions will help ensure your instance runs more smoothly without frequent interruptions.

---

Why This Matters

High CPU Steal Time can severely impact your server's performance, leading to delays in application response times, degraded user experience, and potential revenue losses if your services are customer-facing. Proactively addressing this issue ensures consistent performance, allowing you to maintain reliability and meet your business goals effectively.

---

Key Terms

• CPU Steal Time: The percentage of CPU time that an instance is ready to execute but is waiting for the hypervisor to allocate CPU resources.
• t2.micro: A burstable performance instance in AWS with limited baseline CPU credits and constrained resources.
• Burstable Performance: Instances that can temporarily increase CPU performance using CPU credits accumulated during low usage.
• Placement Groups: Logical groups of instances within a single Availability Zone for optimal network performance.
• Spot Instances: A cost-effective option where AWS can interrupt the instance when capacity is needed elsewhere, potentially suitable for non-critical workloads.

---

The Solution (Our Recipe)

Steps at a Glance:

1. Monitor CPU Steal Time with CloudWatch Metrics.
2. Investigate the hypervisor and host behavior using AWS support tools.
3. Optimize the instance placement or switch to a different instance type.
4. Consider upgrading to a higher-performance instance or migrating to a dedicated host.
5. Explore cost-effective alternatives like Spot Instances or auto-scaling.

---

Step-by-Step Guide:

1. Monitor CPU Steal Time with CloudWatch Metrics
   Use AWS CloudWatch to track the Steal CPU metric for your instance. This helps confirm if the issue is persistent and quantify the impact.

   • Navigate to CloudWatch in the AWS Management Console.
   • Go to Metrics > EC2 > Per-Instance Metrics.
   • Add the CPUSteal metric to a dashboard for visibility.

   For a hands-on approach, use the AWS CLI to fetch metrics:

   aws cloudwatch get-metric-statistics \
     --metric-name CPUUtilization \
     --namespace AWS/EC2 \
     --statistics Average \
     --dimensions Name=InstanceId,Value=INSTANCE_ID \
     --start-time 2025-01-10T00:00:00Z \
     --end-time 2025-01-11T00:00:00Z \
     --period 3600

   Alternatively, you can use Python with the AWS SDK (Boto3) for more automation:

   import boto3
   import datetime
   
   client = boto3.client('cloudwatch')
   
   response = client.get_metric_statistics(
       Namespace='AWS/EC2',
       MetricName='CPUSteal',
       Dimensions=[
           {'Name': 'InstanceId', 'Value': 'INSTANCE_ID'}
       ],
       StartTime=datetime.datetime.utcnow() - datetime.timedelta(days=1),
       EndTime=datetime.datetime.utcnow(),
       Period=3600,
       Statistics=['Average']
   )
   
   for datapoint in response['Datapoints']:
       print(f"Time: {datapoint['Timestamp']}, Steal: {datapoint['Average']}")

---

2. Investigate the Host Behavior
   If high Steal Time persists, request assistance from AWS Support to investigate the host's behavior. You can open a support ticket:

   Dear AWS Support,  
   My `t2.micro` instance in `us-east-2b` frequently experiences high CPU Steal Time, severely degrading performance. Could you investigate the underlying host for any contention or issues?  
   Thank you!  

---

3. Optimize Instance Placement or Switch to a Different Instance Type
   • Stop and start the instance to move it to a different physical host.
   • Test moving the instance to another Availability Zone (e.g., us-east-2a) to reduce potential contention.
   • Use Placement Groups if you have multiple instances that need consistent performance.

---

4. Upgrade to a Higher-Performance Instance or Dedicated Host
   • Consider switching to a t3.micro or higher instance type. T3 instances offer better baseline performance and cost efficiency.
   • For isolation, migrate to a Dedicated Host, which ensures no other tenants share the same physical hardware.

---

5. Explore Cost-Effective Alternatives
   • Use Spot Instances for non-critical workloads that tolerate occasional interruptions. Spot Instances provide significant cost savings while reducing host contention.
   • Implement Auto Scaling to dynamically adjust your instance capacity based on demand, ensuring better resource allocation.

---

Closing Thoughts

Addressing high CPU Steal Time is essential for ensuring your server’s consistent performance. By monitoring your metrics, investigating hypervisor issues, optimizing placement, and considering upgrades or alternative instance types, you can achieve better reliability for your workload.

For more details, check out:

• Amazon EC2 Instance Types
• Understanding Burstable Performance Instances
• Using Placement Groups
• Spot Instances Overview
• Auto Scaling Basics

---

Farewell

I hope this guidance helps resolve the issue and ensures smoother operation for your server! Let me know if you need more details or assistance. Best of luck, Flower Shop Guy! 🌻😊

---

Cheers,

Aaron 😊